Most traditional approaches to probabilistic planning in relationally specified MDPs rely on grounding the problem w.r.t. specific domain instantiations, thereby incurring a com...
We consider the approximate nearest neighbour search problem on the Hamming cube {0, 1}d. We show that a randomised cell probe algorithm that uses polynomial storage and word size...
Indicator-based algorithms have become a very popular approach to solve multi-objective optimization problems. In this paper, we contribute to the theoretical understanding of alg...
Partially observable Markov decision processes (POMDPs) provide an elegant mathematical framework for modeling complex decision and planning problems in stochastic domains in whic...
Partially observable decentralized decision making in robot teams is fundamentally different from decision making in fully observable problems. Team members cannot simply apply si...
Rosemary Emery-Montemerlo, Geoffrey J. Gordon, Jef...